In a world where connectivity is becoming commonplace, there are a multitude of devices that integrate speech recognition technology to improve the human-machine interface that exists between a user and connected devices. For example, in a vehicle, a navigation system, an infotainment system, a climate control system, or other vehicle operations may all be controlled using speech recognition technology. In a connected home, household items such as televisions, clocks, appliances, light switches, thermostats and vacuum cleaners may integrate speech recognition technology. Other portable devices such a personal assistants, smart watches, tablets, mobile phones, to name just a few, also integrate speech recognition technology.
In current practices for devices, a single speech recognition engine is responsible for automatic speech recognition and semantic understanding functions. However, speech recognition engines are known to be less than completely accurate and frequently fail to recognize or identify errors in natural language processing.
There is a need to improve the accuracy of natural language processing used in speech recognition technology.